Stochastic Molecular Reaction Queueing Network Modeling for In Vitro Transcription Process
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To facilitate a rapid response to pandemic threats, this paper focuses on developing a mechanistic simulation model for in vitro transcription (IVT) process, a crucial step in mRNA vaccine manufacturing. To enhance production and support industry 4.0, this model is proposed to improve the prediction and analysis of IVT enzymatic reaction network. It incorporates a novel stochastic molecular reaction queueing network with a regulatory kinetic model characterizing the effect of bioprocess state variables on reaction rates. The empirical study demonstrates that the proposed model has a promising performance under different production conditions and it could offer potential improvements in mRNA product quality and yield.
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